The Role
Build and operate production-grade systems to detect, analyze, and mitigate AI risks in real time. Design backend services, high-throughput post-processing, secure auditable decision paths, and scalable data pipelines. Collaborate with ML and product teams to integrate models, debug end-to-end behavior, and establish safety, versioning, and monitoring best practices.
Summary Generated by Built In
Role Overview
About Realm Labs
Key Responsibilities
Expected Qualifications
Preferred Qualifications
Additional Information
Compensation & Benefits
We are hiring a Founding AI Safety & Systems Engineer to build the core technical systems that detect, analyze, and mitigate AI risks in production.
This role sits at the intersection of Software engineering, ML systems, and AI safety. You will design and implement systems that inspect model behavior, process large-scale signals, and enforce safety and governance policies in real time.
This is not a research-only role. You will focus on turning safety ideas into robust, scalable production systems that enterprises can trust.
This role is ideal for an engineer who understands how modern AI systems work, cares deeply about correctness and robustness, and wants to shape how AI safety is implemented in the real world.
About Realm Labs
Realm Labs is an AI trust and security startup. We help enterprises detect, debug, and prevent AI misbehavior in production through deep inspection, observability, and runtime enforcement. Our systems operate in high-stakes environments where correctness, explainability, and reliability matter.
- Build systems that analyze and evaluate AI behavior at runtime, including:
- Input and output inspection
- Intermediate signal processing
- Policy and risk evaluation pipelines
- Design and implement backend services that support:
- Real-time moderation and safety decisions
- High-throughput model post-processing
- Secure, auditable decision paths
- Work closely with ML and product teams to:
- Translate safety requirements into system designs
- Integrate models, probes, and classifiers into production
- Debug model and system behavior end-to-end
- Implement scalable data pipelines using:
- Python, Go, Rust, and C++
- PostgreSQL, document databases, Elasticsearch, and similar systems
- Build infrastructure that emphasizes:
- Correctness over heuristics
- Clear failure modes and graceful degradation
- Strong observability and explainability
- Establish best practices for:
- Evaluating and validating safety systems
- Versioning and rolling out safety logic
- Monitoring regressions and edge cases
Expected Qualifications
- 5+ years of professional software engineering experience
- Strong backend or systems engineering background
- Experience building production systems with strict correctness requirements
- Ability to reason about complex system behavior and edge cases
- Comfortable working with ML-adjacent systems, even if not a researcher
Preferred Qualifications
- Experience working on AI safety, trust, or reliability systems
- Familiarity with LLMs, model inference pipelines, or ML evaluation systems
- Experience processing large-scale structured and unstructured data
- Strong interest in AI governance, safety, or responsible deployment
- Startup experience or ownership of greenfield systems
Additional Information
- This is a founding role with direct influence on product direction
- You will own systems end-to-end, from design to production
- You will help define how AI safety is implemented at scale
Compensation & Benefits
- Market-aligned compensation
- Significant founding engineer equity
- Medical, Dental, Vision, Life insurance, 401(k), in-office lunch, etc.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for this role and candidate. But if we make you an offer, we will make all reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
CompensationThe base pay range for this role is $180,000 – $240,000 per year.
Skills Required
- 5+ years of professional software engineering experience
- Strong backend or systems engineering background
- Experience building production systems with strict correctness requirements
- Ability to reason about complex system behavior and edge cases
- Comfortable working with ML-adjacent systems
- Experience with Python
- Experience with Go
- Experience with Rust
- Experience with C++
- Experience with PostgreSQL
- Experience with document databases
- Experience with Elasticsearch
- Experience working on AI safety, trust, or reliability systems
- Familiarity with LLMs, model inference pipelines, or ML evaluation systems
- Experience processing large-scale structured and unstructured data
- Strong interest in AI governance, safety, or responsible deployment
- Startup experience or ownership of greenfield systems
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The Company
What We Do
Realm Labs is an AI security company focused on helping enterprises secure and monitor AI applications and data. It develops an AI-based authorization platform designed to prevent data leaks and enable secure generative AI usage with features like agent security and guardrails.
